Python 为什么我的pandas代码会引发分配警告并运行缓慢?
我正在做一个项目,我必须处理很多诊断。无论目的是什么,就编码而言,我认为下面的代码是正确的,但是它需要花费很多时间(~1h),并且它总是向我显示警告。有什么我做得不对的吗?先谢谢你Python 为什么我的pandas代码会引发分配警告并运行缓慢?,python,pandas,loops,dataframe,warnings,Python,Pandas,Loops,Dataframe,Warnings,我正在做一个项目,我必须处理很多诊断。无论目的是什么,就编码而言,我认为下面的代码是正确的,但是它需要花费很多时间(~1h),并且它总是向我显示警告。有什么我做得不对的吗?先谢谢你 # The first 3 values are the only that matters diagnoses_sec = df[['Diagnóstico 2', 'Diagnóstico 3', 'Diagnóstico 4', 'Diagnóstico 5', 'Diagnóstico 6',
# The first 3 values are the only that matters
diagnoses_sec = df[['Diagnóstico 2', 'Diagnóstico 3', 'Diagnóstico 4', 'Diagnóstico 5', 'Diagnóstico 6',
'Diagnóstico 7', 'Diagnóstico 8', 'Diagnóstico 9', 'Diagnóstico 10', 'Diagnóstico 11', 'Diagnóstico 12',
'Diagnóstico 13', 'Diagnóstico 14', 'Diagnóstico 15', 'Diagnóstico 16', 'Diagnóstico 17', 'Diagnóstico 18',
'Diagnóstico 19', 'Diagnóstico 20']]
for i in range(0, diagnoses_sec.shape[1]):
diagnoses_sec.iloc[:,i].fillna("ZZZ", inplace = True)
diagnoses_sec.iloc[:,i] = diagnoses_sec.iloc[:,i].str.slice(start=0, stop=3, step=1)
在这一部分中,有一个警告,但我不明白为什么:
C:\Users\Asus\Anaconda3\lib\site-packages\pandas\core\indexing.py:630: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
self.obj[item_labels[indexer[info_axis]]] = value
守则的第二部分是:
from bisect import bisect_left
diag_icd10_ranges = ["B99","D49","D89","E89","F99","G99","H59","H95",
"I99","J99","K95", "L99", "M99", "N99","O9A","P96","Q99",
"R99","T88","Y99","Z99","ZZZ"]
diag_icd10_dict = {0: 'infectious_icd10d', 1: 'neoplasms_icd10d', 2: 'blood_icd10d', 3: 'endocrine_icd10d',
4: 'mental_icd10d', 5: 'nervous_icd10d', 6: 'eye_icd10d', 7: 'ear_icd10d',
8: 'circulatory_icd10d', 9: 'respiratory_icd10d', 10: 'digestive_icd10d', 11: 'skin_icd10d',
12: 'musculo_icd10d', 13: 'genitourinary_icd10d', 14: 'pregnancy_icd10d', 15: 'perinatalperiod_icd10d',
16: 'congenital_icd10d',
17: 'abnormalfindings_icd10d', 18:'injury_icd10d', 19:'morbidity', 20:'healthstatus', 21:'Nan_Category'}
# function to categorize every patient
def icdGroup(code): return bisect_left(diag_icd10_ranges,code)
# loop for the categorisation of every patient in every diagnose
for i_diag_sec in range(0,diagnoses_sec.shape[1]):
for i_within_diag_sec in range(0, len(diagnoses_sec)):
diagnoses_sec.iloc[i_within_diag_sec,i_diag_sec] = icdGroup(diagnoses_sec.iloc[i_within_diag_sec,i_diag_sec])
我还有一个警告:
C:\Users\Asus\Anaconda3\lib\site-packages\ipykernel_launcher.py:20: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
您将通过CopyWarning获得这些
设置
警告消息,因为Diagnostics_sec
是df
的一部分的副本;在此副本上设置值会引发警告,以确保您知道这一点-您的更改不会传播回df
。如果使用该方法显式复制,这些警告将消失,例如:
diagnoses_sec = df[['Diagnóstico 2', 'Diagnóstico 3']].copy()
关于执行代码所需的时间,以这种方式在数据帧上迭代是低效的,您应该努力使用矢量化操作,将函数或操作应用于整个数组
您可以修改第一个示例来执行此操作:
diagnoses_sec = df[['Diagnóstico 2', 'Diagnóstico 3', 'Diagnóstico 4', 'Diagnóstico 5', 'Diagnóstico 6',
'Diagnóstico 7', 'Diagnóstico 8', 'Diagnóstico 9', 'Diagnóstico 10', 'Diagnóstico 11', 'Diagnóstico 12',
'Diagnóstico 13', 'Diagnóstico 14', 'Diagnóstico 15', 'Diagnóstico 16', 'Diagnóstico 17', 'Diagnóstico 18',
'Diagnóstico 19', 'Diagnóstico 20']].copy()
diagnoses_sec.fillna("ZZZ", inplace=True)
diagnoses_sec = diagnoses_sec.apply(lambda x: x.str.slice(start=0, stop=3, step=1))
这里,fillna
应用于整个数据帧
,并将每个NA
值替换为“ZZZ”
。在第二个操作中,将通过lambda
函数对诊断的每一列(系列
)执行字符串切片操作
第二种情况类似,但由于icdGroup
函数未矢量化(它不在DataFrame
或Series
上运行),并且应用于DataFrame
的每个单元格,因此可以使用对每个值执行它:
diagnoses_sec = diagnoses_sec.applymap(icdGroup)
非常感谢@dspencer!你不知道你帮了我多少忙!我不知道!